The phrase "hypothesis true" is grammatically correct and can be used in written English.
It is typically used to refer to the belief or statement being tested in a scientific or research setting. Example: The results of the experiment supported the hypothesis proposed by the researchers, proving it to be true.
This is neat, but it raises a whole new question: why is the past hypothesis true?
On the other hand, if the experiment showed the test implications to be true, this did not prove the hypothesis true.
The abstract entity corresponding to ZFC, for instance, is partial in the sense that it neither makes the continuum hypothesis true nor false.
Null hypothesis: true area = 0.5.
Null hypothesis: true area under ROC curve = 0.5.
aUnder the nonparametric assumption bNull hypothesis: true AUC = 0.5 a.
The results proved both hypotheses true, showing that estimations were more accurate and consistent for models calibrated using actual occupancy compared with those using assumed occupancy, and that cross-ECM estimation resulted in statistical inaccuracy.
A P-value less than 0.05 combined with a Bayes factor greater than 1.0 obtained from the observed data render more credit to the null hypothesis being true than the alternative hypothesis being true.
Suppose that for m 1 tests the null hypothesis is true and for m 2 tests the alternative hypothesis is true.
The optimal, modified two-stage Simon design tested these hypotheses with 0.05 probability of accepting a dose escalation strategy if the null hypothesis was true and 0.80 probability of rejecting the strategy if the alternative hypothesis was true.
The likelihood ratio is defined as the likelihood that the evidence would be observed if the same-origin hypothesis were true divided by the likelihood that the evidence would be observed if the different-origin hypothesis were true [7-11].
